<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="utf-8">
    <meta http-equiv="X-UA-Compatible" content="IE=edge">
    <meta name="viewport" content="width=device-width, initial-scale=1">
    <META NAME="ROBOTS" CONTENT="NOINDEX, NOFOLLOW">
    <link rel="icon" href="../images/logo/logo.png" type="image/x-icon">
    <link rel="shortcut icon" href="../images/logo/logo.png"
          type="image/x-icon">
    <title>浏阳德塔软件开发有限公司 女娲计划</title>
</head>
<body style="Max-width: 700px; text-align:center; margin:auto;">
<div style="text-align:left; Max-width: 680px; margin-left:15px;">
    <a href="../">上一页</a>
    <br/>
    <br/>
    <br/>第十章_DNA非卷积视觉技术
    <br/> 作者: 罗瑶光, Author:Yaoguang.Luo<br/>
    <br/>
    <br/>
    <br/>费洛蒙的计算方式
    <br/>
    <br/>1 CNN卷积元基PDC扩展. refer page 774
    <br/>
    <br/>2 邻近元基PDC代谢 共同基. refer page 774
    <br/>
    <br/>3 PDC链结构rotation. refer page 774
    <br/>
    <br/>4 丝化散开与腐蚀. refer page 775
    <br/>
    <br/>Pheromone Computing.
    <br/>
    <br/>The value contributions of pheromone computing in a domain of
    non-biology-chemistry, it mainly to be an ordinary machine to observe
    the DNA encoding and meta-base indexing. According to this DNA and PDN
    with their indexing and optimizing, the author continuing to find a PDN
    metabolism on software coding. After three years software designing and
    based on multi-proofs, the author proves the metabolism of software is
    similar to the metabolism of biology. (Indexing optimization, high
    frequency priority, same features filtering, as a slang "the survival
    of the fittest”).

    <br/>
    <br/>(下图的丝化是元基的概率组合的归纳如矩阵的新陈代谢模拟发散. 不是肽展公式PDS丝化过程.
    下图的1和2, 作者认为是一种比较合乎情理的又具有代表性的概率矩阵组合归纳.
    罗瑶光补充20220307，见抖音20201205笔记)
    <img class="banner_img" style="width: 100%" src="../images/5_7108/10/10_9.jpg"
         alt="浏阳德塔软件开发有限公司,罗瑶光"/>

    <br/>
    <br/>罗瑶光的费洛蒙计算发散
    <br/>
    <br/>费洛蒙计算在非生化研究领域发散的价值, 主要体现在作者第一次有信心进行DNA元基仿生
    进化模拟计算, 如之后的元基索引和 确定索引元基的新陈代谢方式的思维发散. 通过大量证据
    逐步的论证出: 软件的元基索引新陈代谢进化方式, 与生物的进化方式是一致的. 作者感谢下
    斯坦福大学的公开课量子数学,作者的正交计算和观测思维来自量子数学基础.

    <br/>
    <br/>应用
    <br/>
    <br/>1 舌诊观测应用. refer page 736
    <br/>
    <br/>2 骨CT观测应用. refer page 735
    <img class="banner_img" style="width: 100%" src="../images/5_7108/10/10_10.jpg"
         alt="浏阳德塔软件开发有限公司,罗瑶光"/>

    <br/>
    <br/>测试原图来自医学教材
    <br/>
    <br/>3 皮肤病观测应用. refer page 下册156, 下册157
    <br/><img class="banner_img" style="width: 100%" src="../images/5_7108/10/10_11.jpg"
              alt="浏阳德塔软件开发有限公司,罗瑶光"/>

    <br/> 测试原图来自医学教材
    <br/>
    <br/>16元基进制的非卷积算法处理手指疾病图片的真实观测实例, 其推导过程早期测试图片见后面的
    270页.
    <br/>
    <br/>4 图片读脏 应用逻辑
    <img class="banner_img" style="width: 100%" src="../images/5_7108/10/10_12.jpg"
         alt="浏阳德塔软件开发有限公司,罗瑶光"/>
</div>
</body>